import gradio as gr
import warnings
import os
import subprocess
from pathlib import Path
import shutil
import spaces
from atomworks.io.utils.visualize import view
from lightning.fabric import seed_everything
from rfd3.engine import RFD3InferenceConfig, RFD3InferenceEngine
from utils import download_weights
from utils.pipelines import test_rfd3_from_notebook, unconditional_generation
from gradio_molecule3d import Molecule3D


download_weights()

    
# Gradio UI
with gr.Blocks(title="RFD3 Test") as demo:
    gr.Markdown("# RFdiffusion3 (RFD3) for Backbone generation")
    gr.Markdown("Models auto-downloaded on launch. Click to test.")

    
    test_btn = gr.Button("Run RFD3 Test")
    output = gr.Textbox(label="Test Result")
    
    test_btn.click(test_rfd3_from_notebook, outputs=output)

    gr.Markdown("Unconditional generation of backbones")
    with gr.Row():
        num_designs_per_batch = gr.Number(
            value=2,
            label="Number of Designs per Batch",
            precision=0,
            minimum=1,
            maximum=8
        )
        num_batches = gr.Number(
            value=5,
            label="Number of Batches",
            precision=0,
            minimum=1,
            maximum=10
        )
        length = gr.Number(
            value=40,
            label="Length of Protein (number of residues)",
            precision=0,
            minimum=10,
            maximum=200
        )

    gen_directory = gr.State(None)
    gen_results = gr.State(None)
    gen_btn = gr.Button("Run Unconditional Generation")
    #gen_output = gr.Textbox(label="Generation Result")
    gen_btn.click(unconditional_generation, inputs=[num_batches, num_designs_per_batch, length], outputs=[gen_directory, gen_results])


    # New visualize section
    #with gr.Row():
    #    viz_btn = gr.Button("Visualize", visible=True)
    #    batch_dropdown = gr.Dropdown(
    #        choices=[], 
    #        label="Select Batch",
    #        visible=False
    #    )
    #    design_dropdown = gr.Dropdown(
    #        choices=[], 
    #        label="Select Design",
    #        visible=False
    #    )
    #    viewer = Molecule3D(visible=False)
#
    #def toggle_visualize(result):
    #    if result is None:
    #        return gr.Dropdown(visible=False), gr.Dropdown(visible=False), Molecule3D(visible=False)
    #    batches = sorted(list({d["batch"] for d in result}))
    #    return (
    #        gr.update(choices=batches, visible=True),  # Batch dropdown
    #        gr.update(choices=[], visible=True),       # Design empty initially
    #        gr.update(visible=False)
    #    )
#
    #def update_designs(batch, result):
    #    if batch is None:
    #        return gr.update(choices=[])
    #    designs = sorted(list({d["design"] for d in result if d["batch"] == batch}))
    #    return gr.update(choices=designs)
#
    #def load_viewer(batch, design, result):
    #    if batch is None or design is None:
    #        return gr.update(visible=False)
    #    pdb_data = next(d["pdb"] for d in result if d["batch"] == int(batch) and d["design"] == int(design))
    #    return gr.update(value=pdb_data, visible=True, reps=[{"style": "cartoon"}])  # Customize style
#
    ## Events
    #viz_btn.click(toggle_visualize, inputs=gen_directory, outputs=[batch_dropdown, design_dropdown, viewer])
    #batch_dropdown.change(update_designs, inputs=[batch_dropdown, gen_directory], outputs=design_dropdown)
    #batch_dropdown.select(fn=update_designs, inputs=[batch_dropdown, gen_directory], outputs=design_dropdown)  # For selection
    #gr.Dropdown.select(update_designs, batch_dropdown, design_dropdown).then(  # Chain
    #    lambda b, d, r: load_viewer(b, d, r),
    #    inputs=[batch_dropdown, design_dropdown, gen_directory],
    #    outputs=viewer
    #)

    

if __name__ == "__main__":
    demo.launch()